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therapeutic targets. Develops and applies machine learning and statistical modeling approaches for biomarker discovery, classification, prediction, and patient stratification. Develops algorithms and
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(AI) and machine learning (ML) methodologies. The position involves annotating clinical data, collaborating with AI/ML/NLP teams, developing algorithms, and generating insights to improve patient care
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(AI) and machine learning (ML) methodologies. The position involves annotating clinical data, collaborating with AI/ML/NLP teams, developing algorithms, and generating insights to improve patient care
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). Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology
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building and applying state-of-the-art machine learning approaches, including foundation models, variational autoencoders (VAEs), and transformer-based architectures, to integrate single-cell and multi-omic
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-generation permanent magnets using a powerful combination of high-throughput computation, machine learning, rapid synthesis and efficient characterization. This position requires expertise in synthesizing and
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clinical or imaging-based research. Familiarity with vascular imaging software, image post-processing, and AI/machine learning applications in clinical or imaging research is desirable. Demonstrates strong
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within the Texas Children's Cancer Center. The project aims to develop and test novel CAR-redirected immunotherapy for pediatric solid tumors. In particular, gene knockout and knock-in screens will be
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imaging software, image post-processing, and AI/machine learning applications in clinical or imaging research is desirable. Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access
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therapies, and machine learning and artificial intelligence. Postdoctoral fellows will join a highly collaborative research environment at Rice, with access to a large and growing synthetic biology community